The strong effect of network resolution on electricity system models with high shares of wind and solar

TL;DR

This paper examines how the spatial resolution of electricity system models significantly impacts cost estimates and investment decisions for wind and solar in Europe's high-renewable power system, highlighting the importance of detailed network modeling.

Contribution

It demonstrates the substantial influence of network resolution on system costs and investment patterns, emphasizing the need for high-resolution models in renewable energy planning.

Findings

Higher resource resolution reduces costs by up to 10%.

Increased network resolution raises costs by up to 23% due to grid bottlenecks.

Grid expansion reduces costs by around 16%, mitigating low-resolution effects.

Abstract

Energy system modellers typically choose a low spatial resolution for their models based on administrative boundaries such as countries, which eases data collection and reduces computation times. However, a low spatial resolution can lead to sub-optimal investment decisions for wind and solar generation. Ignoring power grid bottlenecks within regions tends to underestimate system costs, while combining locations with different wind and solar capacity factors in the same resource class tends to overestimate costs. We investigate these two competing effects in a capacity expansion model for Europe's power system with a high share of renewables, taking advantage of newly-available high-resolution datasets as well as computational advances. We vary the number of nodes, interpolating between a 37-node model based on country and synchronous zone boundaries, and a 1024-node model based on the location of electricity substations. If we focus on the effect of renewable resource resolution and ignore network restrictions, we find that a higher resolution allows the optimal solution to concentrate wind and solar capacity at sites with better capacity factors and thus reduces system costs by up to 10% compared to a low resolution model. This results in a big swing from offshore to onshore wind investment. However, if we introduce grid bottlenecks by raising the network resolution, costs increase by up to 23% as generation has to be sourced more locally at sites with worse capacity factors. These effects are most pronounced in scenarios where grid expansion is limited, for example, by low local acceptance. We show that allowing grid expansion mitigates some of the effects of the low grid resolution, and lowers overall costs by around 16%.